A Prediction Model for Skin Wound Suture Forces With Uncertain Material Parameters

WEN Guangquan; JI Xiaogang; DUAN Yushun; DENG Lin

doi:10.21656/1000-0887.430067

Volume 44 Issue 4

Apr. 2023

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Article Navigation > Applied Mathematics and Mechanics > 2023 > 44(4): 441-449

WEN Guangquan, JI Xiaogang, DUAN Yushun, DENG Lin. A Prediction Model for Skin Wound Suture Forces With Uncertain Material Parameters[J]. Applied Mathematics and Mechanics, 2023, 44(4): 441-449. doi: 10.21656/1000-0887.430067

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A Prediction Model for Skin Wound Suture Forces With Uncertain Material Parameters

doi: 10.21656/1000-0887.430067

1.
School of Mechanical Engineering, Jiangnan University, Wuxi, Jiangsu 214122, P.R.China
2.
Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment & Technology, Wuxi, Jiangsu 214122, P.R.China

Received Date: 2022-03-03
Rev Recd Date: 2022-06-05
Publish Date: 2023-04-01

Abstract

Abstract

To evaluate the forces required for the suture of skin wounds quickly and effectively, the nonlinear finite element method was used to calculate the suture forces for skin wounds with different sizes and material parameters. With the calculated results as samples, the prediction model for skin wound suture forces was constructed by means of the EBF neural network model. Given the uncertain skin material parameters influencing the reliability of numerical results, the Monte-Carlo method was used to analyze the uncertainty propagation of skin material parameters. Finally, the prediction analysis and measuring experiment of wound suture forces were carried out with pig skin specimens to verify the reliability of the method. The results showed that, the suture force increases first and then decreases according to the suture point sequence, and the peak force occurs before the center of the wound. For a 40 mm×10 mm wound, the peak suture force is about 1.7 N, and that for a 40 mm×14 mm wound is about 2.5 N. Influenced by the uncertainty of material parameters, the prediction results of suture forces fluctuate by as much as ±0.6 N. The proposed theoretical prediction model provides an effective solution to the problem of parameter uncertainty propagation for biological soft tissue materials such as skins, and makes an important mechanical reference for robotic surgical suture.
- skin mechanics,
- prediction model for suture force,
- EBF neural network,
- uncertainty propagation

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References(22)

References

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